Newton Fund for capacity building in data intensive science in the Middle-East

Lead Research Organisation: University College London


This project will help create capacity in the application of artificial intelligence and applying big data techniques. These will be critical to enabling the partner countries to apply these advance techniques to solve development challenges in agriculture, healthcare and the environment. It is planned to start the project in Jordan and once the training programmes are established to extend it to Egypt and Turkey.

Planned Impact

The Big Data revolution is everywhere. The Artificial Intelligence approach to data analysis and mining would contribute not only to the Physical Sciences in the Middle East, but also to transportation, the oil industry, health and many other areas. Data science is therefore a key developmental goal for the host countries. The proposed programme will enable a regional capacity building in Jordan (and later Egypt and Turkey) in Artificial Intelligence (AI) through analysing Big Data in Astronomy and Particle Physics. The programme will be modelled on UCL's successful STFC Centre for Doctoral Training in Data Intensive Science (DIS) which included extensive collaboration with hi-tech industry partners. The aim is to extend our UCL CDT-DIS model for collaboration and networking with interested groups in the Middle East, building in research secondments for academics in both the UK and the partner countries.

The programme will provide a world-leading training experience, co-created and co-delivered by industry, which will result in highly
trained and well-rounded AI-experts, with a truly unique skill-set, who will become future AI-leaders in Jordan in both academia and industry, helping address the significant national skills-shortage in this area and driving forward the economy. We will build and existing industrial partners in the UK and extend it to similar companies in Jordan.
As well as numerous economical, educational and cultural benefits from the fundamental research undertaken in
the programme, for instance cutting-edge technology development (such as the World Wide Web, superconductivity and
medical imaging techniques), many of the research projects will have a direct impact.


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Henghes B (2022) Deep learning methods for obtaining photometric redshift estimations from images in Monthly Notices of the Royal Astronomical Society

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Yurchenko S (2023) ExoMol line lists - XLVII. Rovibronic spectrum of aluminium monochloride (AlCl) in Monthly Notices of the Royal Astronomical Society

Description Newton Fund collaboration with the University of Jordan in Amman and the Royal Scientific Society of Jordan 
Organisation University of Jordan
Country Jordan 
Sector Academic/University 
PI Contribution Due to the Covid situation we could not have face-to-face meetings in 2020-2021. Instead we were holding virtual meetings, including an online course on Machine Learning to over 40 Jordanian students (approximately 60% of whom were female) and participation of the Jordanian partners in the UCL CDT seminar series. In July 2022 we host a successful summer school at with 29 Jordanian students. 7 of them stayed for a whole month to work on projects with UCL staff. 3 Jordanian students further visited for a month on in January-February 2023. The project was extended at no-cost until the end of March 2023.
Collaborator Contribution The Jordanian collaborators have helped on running the ML course, and they are providing additional admin support.
Impact The ML training both remotely and in the Summer School in July 2023 has successfully been delivered to Jordanian MSc students. The collaboration is multi-disciplinary, combining Astrophysics, HEP, AI/ML and other fields.
Start Year 2019
Description We held virtual launch events of the UCL-Jordan programme in Feb 2020 (led by Jordan) and in April 2020 (led by UCL) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Virtual launch events of the UCL-Jordan programme in Feb 2020 (led by Jordan) and in April 2020 (led by UCL)
Year(s) Of Engagement Activity 2020